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Label Review Analytics — Record Quality Audit + Date by Category Pivot
x402
Label Review Analytics — Record Quality Audit + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).
Runs two local analytical reports on label review data: a record quality audit and a date-by-category pivot, for up to 200 rows of reviewed_records and changed_labels data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Record quality audit + Date by category pivot: Record quality audit + Date by category pivot for supplied label review records (reviewed_records, changed_labels). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Two independent analytical reports: (1) a record quality audit summarizing data completeness, distributions, and anomalies in the reviewed_records and changed_labels columns; (2) a date-by-category pivot table aggregating the selected field (reviewed_records or changed_labels) across dataset_group and date dimensions. All computation is performed locally on the supplied data with no external lookups.
Example use cases
Annotation pipeline quality check
“I have 150 rows of label review data from my annotation pipeline — each row has a row_id, dataset_group, date, reviewed_records, and changed_labels. Can you run a record quality audit and a date-by-category pivot on this data, focusing on the reviewed_records field?”
Label change rate trend analysis
“Run a date-by-category pivot and a quality audit on my label review records — I want to see how changed_labels vary across my dataset groups (group-a and group-b) over the past month, up to 120 rows.”
Multi-group annotation audit
“I need a two-report analytics bundle for my label review dataset: a record quality audit and a date pivot grouped by category, using the changed_labels field. I have about 80 rows across three dataset groups — can you generate both reports at once?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-017?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have label review or annotation QA data with reviewed_records and changed_labels columns and need both a quality audit and a date-by-category pivot in a single $0.01 call for up to 200 rows. Prefer this over generic analytics tools when your data fits the label review schema exactly and you want two bundled reports without setting up external pipelines or paying for live lookup or prediction services.
Side effects
- Exceeds 200-row limit — request rejected or truncated
- Invalid date format (not YYYY-MM-DD) — row rejected or validation error
- Missing required fields (row_id, dataset_group, date, reviewed_records, changed_labels) — row skipped or error returned
- Null numeric values in both metric fields — audit may flag incomplete data quality
- field enum value not one of reviewed_records or changed_labels — validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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